New semiparametric estimators transport causal effects more efficiently via mediators
RexDouglass · x · 2026-10-25
A new arXiv paper (stat.ME, by Zhang, Rudolph, Díaz et al.) tackles transporting average treatment effects estimated in trials to a target population more efficiently.
- Proposes two flexible semiparametric estimators: a one-step estimator that assumes knowledge of the baseline covariates driving cross-population heterogeneity and transports only through them (instead of the full covariate set), plus a collaborative one-step estimator that needs no such prior knowledge.
- Improves efficiency under mediation and intermediate confounding via targeted dimension-reduction strategies.
- Finite-sample performance is examined via simulation, and the estimators are applied to a large housing-mobility trial (MTO) and a hearing intervention trial (ACHIEVE).
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